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How does Snowflake compare to Microsoft's T-SQL for SQL Server? Part three of a five-part series of blogs |
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All dialects of SQL are similar, you'd think, but the different ethos and editing environment of Snowflake versus SQL Server make the switch surprisingly difficult, as this blog explains.
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Most people who write SQL in SQL Server do it through SQL Server Management Studio (SSMS). Most people who write SQL in Snowflake do it through Snowsight, the web-based Snowflake interface.

The two environments compared. They are very different!
However, it's the completely different business model which makes transitioning from T-SQL to Snowflake SQL tricky. Although Snowflake (obviously) contains databases, you also need to know about some other concepts:
Concept | Notes |
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Warehouses | These are places in which you run queries on a pay-per-use basis (effectively they're CPUSs for hire). |
Roles | You can't do anything in Snowflake until you've said what role you will play in accessing data. |
So in order to run a typical Snowflake query, you often have to say which warehouse and role you're using. For example:

The selected commands make sure that we're using the correct computing area and role.
This all makes getting started with Snowflake a bit harder than getting started with SSMS.
One other huge difference behind-the-scenes which probably won't affect you, but is nice to know: Snowflake stores data in columns, whereas SQL Server stores data in rows (so you can't index columns in Snowflake, for example).
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